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Modeling the Supply of Renewable Electricity to Metropolitan Regions in China

Xiao, Mengzhu and Wetzel, Manuel and Pregger, Thomas and Simon, Sonja and Scholz, Yvonne (2020) Modeling the Supply of Renewable Electricity to Metropolitan Regions in China. Energies. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/en13123042. ISSN 1996-1073.

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Official URL: https://www.mdpi.com/1996-1073/13/12/3042#cite

Abstract

The accelerated urbanization and industrialization in China is leading to major challenges due to rising energy demand and emissions. Cities in particular play an important role in the decision-making and implementation processes for the energy transition. However, they often have only limited local energy potential and are heavily dependent on supply regions. We therefore assess how a predominantly renewable power supply can be implemented based on the availability of local or imported renewable resources. We present a case study in which an advanced energy system model is parametrized and applied to address questions which are relevant to the transformation of the energy system in China. The model is capable of simultaneously optimizing investment decisions and hourly power balances of a scenario year, taking into account different storage technologies, regional power exchange and policy constraints such as carbon cap, carbon price and renewable portfolio standards. The study takes the Beijing-Tianjin-Hebei metropolitan region with Inner Mongolia as a supply region—considered as exemplary regions characterized by heterogeneous infrastructures, resources and consumption—as its model. Starting from a context-related normative energy scenario, we analyze a possible future electricity system under various assumptions using the Renewable Energy Mix (REMix) energy system model developed at the DLR (German Aerospace Center). Depending on the estimated potentials of renewable energies, technology costs and the projected electricity demand, the metropolitan region is mainly supplied with imported wind and solar power. A sensitivity analysis considers installed capacities, annual generation, CO2 emissions and costs. The results indicate that the assumption of storage costs is of great importance for the future total costs of an electricity system. Variations in other parameters led to different generation portfolios with similar system costs. Our results provide insights into future regional infrastructure needs, and underline the importance of regional coordination and governance for the energy transition in China.

Item URL in elib:https://elib.dlr.de/139739/
Document Type:Article
Title:Modeling the Supply of Renewable Electricity to Metropolitan Regions in China
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Xiao, MengzhuMengzhu.Xiao (at) dlr.dehttps://orcid.org/0000-0001-7591-0306
Wetzel, ManuelManuel.Wetzel (at) dlr.dehttps://orcid.org/0000-0001-7838-2414
Pregger, ThomasThomas.Pregger (at) dlr.dehttps://orcid.org/0000-0002-6728-7451
Simon, SonjaSonja.Simon (at) dlr.dehttps://orcid.org/0000-0003-2775-5457
Scholz, YvonneYvonne.Scholz (at) dlr.dehttps://orcid.org/0000-0002-1633-3825
Date:12 June 2020
Journal or Publication Title:Energies
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.3390/en13123042
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:1996-1073
Status:Published
Keywords:energy system modeling; power system optimization; sensitivity analysis; metropolitan region; energy transition; renewable energy
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Systems Analysis and Technology Assessment (old)
Location: Stuttgart
Institutes and Institutions:Institute of Engineering Thermodynamics > Energy Systems Analysis
Deposited By: Xiao, Mengzhu
Deposited On:16 Dec 2020 20:13
Last Modified:16 Dec 2020 20:13

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